[D] Data science is not software engineering and treating it as such is suboptimal at best. (Please) change my mind.
I have recently written a blog post on medium describing why I feel that there has to be room for science in data science and how one approach that helps solve this problem is proper experiment management.
I would love to hear your thoughts on the subject.
What are the best practices in your organizations/teams and how do they differ from classical software development approaches?